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Predicting Damage Evolution in Composites with Explicit Representation of Discrete Damage Modes

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Abstract

Polymer matrix composites (PMCs) are playing rapidly increasing roles in future military and civilian industries. Damage tolerance analysis is an integral part of PMC structural design. Considerable research efforts have been invested to establish predictive capabilities, but thus far high-fidelity strength and durability prediction capabilities are yet to be established. Advanced numerical methods that can explicitly resolve the multiple-damage processes and their nonlinear coupling at various scales are highly desired. This paper first reviews the recent development of advanced numerical methods, including eXtended Finite Element Method (X-FEM), phantom node methods (PNM), and the Augmented Finite Element Method (A-FEM), in handling the multiple-damage coupling in composites. The capability of these methods in representing various composite damage modes explicitly with embedded nonlinear fracture models (such as cohesive zone models) makes them excellent candidates for high-fidelity failure analyses of composites. The detailed formulation of A-FEM and its implementation to a popular commercial software package (ABAQUS) as a user-defined element has been given. Successful simulations of composites at various scales using the framework of A-FEM are presented and the numerical and material issues associated with these high-fidelity analyses are discussed. Through the numerical predictions and the direct comparisons to experimental results, it has been demonstrated that high-fidelity failure analyses can be achieved with the A-FEM through careful calibration of nonlinear material properties and cohesive fracture parameters and with proper considerations of the different length scales within which these damage processes operate.

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Yang, Q.D., Do, B.C. (2014). Predicting Damage Evolution in Composites with Explicit Representation of Discrete Damage Modes. In: Voyiadjis, G. (eds) Handbook of Damage Mechanics. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8968-9_16-1

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